Data Scientist

Our client is seeking an experienced Data Scientist to develop and enhance data-driven forecasting solutions within a growing technology environment.

This role will suit someone with a strong background in statistical modelling, machine learning and time-series analysis who enjoys transforming complex datasets into practical insights. You will work closely with technical colleagues, customers and business stakeholders to deliver forecasting solutions that support real-world decision-making., * Explore and analyse large, complex datasets to identify trends, patterns and commercially valuable insights.

• Develop, test and optimise statistical and machine learning models, with a particular focus on time-series forecasting.
• Select appropriate modelling approaches and evaluate performance using relevant validation techniques and metrics.
• Carry out feature engineering, data preparation and exploratory data analysis to improve model outcomes.
• Communicate findings and translate technical results into clear, actionable recommendations for customers and non-technical stakeholders.
• Work with engineering colleagues to integrate and deploy data science models into production environments.
• Support model monitoring, retraining and ongoing performance improvement.
• Collaborate with internal teams to ensure data science solutions align with business and customer requirements.
• Contribute to the development of data science standards, tools and best practices as the team grows.
• Stay informed of developments in forecasting, machine learning and applied data science.

• A minimum of 3 years’ experience in a Data Scientist, Applied Scientist, Machine Learning Scientist or closely related analytical role.
• Practical experience developing machine learning or statistical models for time-series forecasting.
• Strong knowledge of statistics, machine learning principles, experimental methods and model evaluation techniques.
• Proficiency in Python and commonly used data science libraries such as pandas, NumPy, scikit-learn or similar.
• Experience preparing, processing and analysing structured datasets.
• Strong exploratory data analysis and feature engineering capabilities.
• Ability to interpret model outputs and communicate findings clearly to technical and non-technical audiences.
• Experience contributing to end-to-end data science projects, from problem definition and data exploration through to model evaluation and implementation.
• Ability to work independently while contributing effectively within a collaborative technical team.

Desirable Skills

• Experience supporting the deployment or ongoing monitoring of data science models in production.
• Familiarity with MLOps practices and automated model pipelines.
• Experience with cloud platforms such as AWS, Azure or Google Cloud Platform.
• Knowledge of SQL and data visualisation tools.
• Familiarity with forecasting libraries or techniques such as ARIMA, Prophet, gradient boosting or deep-learning-based forecasting.
• Understanding of data engineering processes and scalable data pipelines.
• Experience working with computer vision or other applied machine learning models.
• Previous experience in a customer-facing technical or analytical position.
• An interest in progressing towards technical leadership, data science leadership or management.

Educational Requirements

• A third-level degree in Data Science, Statistics, Mathematics, Computer Science, Artificial Intelligence, Engineering, Economics or another quantitative discipline.
• A postgraduate qualification in a relevant subject would be beneficial but is not essential.
• Relevant professional experience may also be considered in place of a specific academic background.

• Permanent position.
• Standard Monday-to-Friday working hours.
• Flexible or hybrid working arrangements, subject to business requirements.
• Competitive salary and benefits package.
• Opportunities for professional development and progression into technical leadership.
• Exposure to modern data science technologies and high-impact customer projects.
• The opportunity to help shape data science practices within a growing team.